{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:HMKP6KYADFCPP4SBEN4B5MCZQR","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9553bc7b8ceba60182abc47ccbe1ae9a5cd025d666b1067d1faead821843ff83","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-11T01:01:54Z","title_canon_sha256":"99fa91a7289b789f7ce33e8ca9fa61be3e38a9dbeae163daf24d6cc161d1e7c7"},"schema_version":"1.0","source":{"id":"2012.06063","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.06063","created_at":"2026-07-05T02:58:05Z"},{"alias_kind":"arxiv_version","alias_value":"2012.06063v1","created_at":"2026-07-05T02:58:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.06063","created_at":"2026-07-05T02:58:05Z"},{"alias_kind":"pith_short_12","alias_value":"HMKP6KYADFCP","created_at":"2026-07-05T02:58:05Z"},{"alias_kind":"pith_short_16","alias_value":"HMKP6KYADFCPP4SB","created_at":"2026-07-05T02:58:05Z"},{"alias_kind":"pith_short_8","alias_value":"HMKP6KYA","created_at":"2026-07-05T02:58:05Z"}],"graph_snapshots":[{"event_id":"sha256:68cb7a018a46967bed633608ee6c7fe0a04a99f4bd173d5ddd46d1e791b7dfe0","target":"graph","created_at":"2026-07-05T02:58:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2012.06063/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Matrix completion has received vast amount of attention and research due to its wide applications in various study fields. Existing methods of matrix completion consider only nonlinear (or linear) relations among entries in a data matrix and ignore linear (or nonlinear) relationships latent. This paper introduces a new latent variables model for data matrix which is a combination of linear and nonlinear models and designs a novel deep-neural-network-based matrix completion algorithm to address both linear and nonlinear relations among entries of data matrix. The proposed method consists of two","authors_text":"Mohammad Hossein Kahaei, Saeid Mehrdad","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-11T01:01:54Z","title":"Deep Learning Approach for Matrix Completion Using Manifold Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.06063","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:5cdaab86553cec2bc75093986a408cebfa23b37ef272620a77c4d77f6edf3077","target":"record","created_at":"2026-07-05T02:58:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9553bc7b8ceba60182abc47ccbe1ae9a5cd025d666b1067d1faead821843ff83","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-11T01:01:54Z","title_canon_sha256":"99fa91a7289b789f7ce33e8ca9fa61be3e38a9dbeae163daf24d6cc161d1e7c7"},"schema_version":"1.0","source":{"id":"2012.06063","kind":"arxiv","version":1}},"canonical_sha256":"3b14ff2b001944f7f24123781eb059845a184fddf4b27878733dd91c38c58bd2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3b14ff2b001944f7f24123781eb059845a184fddf4b27878733dd91c38c58bd2","first_computed_at":"2026-07-05T02:58:05.222544Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:58:05.222544Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QBapXcwFDHzmGvnVRc0OSNzOoNDX4rjeanqlIzCd05PQcpe2q3Ek3vklIQivCLwJvQ1pT9LGwXzl5/EmREM2DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:58:05.223051Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.06063","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5cdaab86553cec2bc75093986a408cebfa23b37ef272620a77c4d77f6edf3077","sha256:68cb7a018a46967bed633608ee6c7fe0a04a99f4bd173d5ddd46d1e791b7dfe0"],"state_sha256":"98e22400e20051ebb000f1400e1870b496c1e30a1301fb2b73019580aa187c44"}